Remote | Senior Software Engineer — $100–$150/hour

24-Mag•New York, NY

5d•$100 - $150•Remote

About The Position

We are sharing a specialised consulting opportunity for experienced Senior Software Engineers with strong expertise in software development, debugging, feature implementation, codebase refactoring, performance optimisation, algorithms, and production-quality engineering to contribute to an advanced AI training and reinforcement-learning environment project. Selected professionals will create reproducible reinforcement-learning environments that test advanced AI systems on realistic software-engineering problems involving bug fixing, feature development, refactoring, and performance optimisation. The work requires strong technical judgement, robust reference solutions, and clear documentation of implementation decisions. No prior experience in AI is required.

Requirements

Significant hands-on expertise in at least one of Python 3, Java, Rust, Go, C++, or TypeScript
Strong understanding of algorithms, data structures, and core software-engineering principles
Proven ability to debug complex systems and resolve difficult software defects
Strong feature-development experience across production codebases
Experience refactoring large or legacy codebases
Demonstrated performance-optimisation experience
Ability to understand and work effectively within unfamiliar codebases
Track record of delivering high-impact features from conception through implementation
Strong judgement around code quality, maintainability, and reliability
Ability to design reproducible technical environments and reference solutions
Strong technical documentation and written communication skills
Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party

Nice To Haves

Experience reviewing or validating other engineers' code is advantageous
Curiosity about AI systems and technical evaluation is beneficial

Responsibilities

Create realistic reinforcement-learning environments based on software-engineering problems
Design tasks involving bug fixing, feature implementation, refactoring, and optimisation
Build reproducible technical environments with clearly defined expected outcomes
Develop golden reference solutions demonstrating correct implementations
Ensure tasks reflect authentic engineering challenges across varied codebases
Analyse and troubleshoot complex software defects
Identify root causes across unfamiliar or evolving codebases
Develop reliable fixes while preserving existing system behaviour
Apply structured debugging strategies to technically difficult problems
Validate solutions for correctness, maintainability, and unintended regressions
Implement robust features across existing software systems
Apply sound algorithms, data structures, and software-engineering principles
Design solutions with scalability and long-term maintainability in mind
Follow established engineering practices and code-quality standards
Contribute expert-level implementation approaches across supported languages
Refactor legacy or complex code to improve clarity and maintainability
Identify performance bottlenecks and inefficient implementation patterns
Optimise code for execution efficiency and system reliability
Support modernisation of existing software architectures where appropriate
Balance performance improvements with readability and technical quality
Document technical reasoning, implementation choices, and solution approaches
Review and validate technical submissions for correctness and clarity
Evaluate peer-contributed code against project requirements
Provide structured feedback on weak or incomplete engineering solutions
Maintain clear technical documentation supporting reproducibility and AI evaluation